Unless otherwise indicated herein, the materials described in this section are not prior art to the claims in this application and are not admitted to be prior art by inclusion in this section.
Power spectral density (PSD) estimation has wide applications in industry. Spectrum sensing in cognitive radio (CR) demands an accurate determination of PSD of a signal. CR improves spectrum utilization by allowing secondary users to access unused licensed spectrum. The unused sub-bands are found using spectrum sensing. Accurate PSD estimation is also in demand with femto-cell base stations in self-organizing networks for next generation cellular wireless technology.
A first step in spectrum sensing is the power spectral density (PSD) estimation. Conventional Welch's method was proposed for spectrum sensing for CR. Welch's method is an example of Discrete Fourier Transform (DFT) based PSD estimation. In Welch's method, the received signal samples are segmented into a few segments. The estimated PSD is achieved by linearly averaging the periodograms of all segments. Additional averaging (i.e. additional segments) leads to lower estimation variance of the PSD. Alternatively, longer segments lead to a better frequency resolution. Therefore, for the same number of received signal samples, there is a trade-off between estimation accuracy and frequency resolution.